Variable Focus Liquid Lens Optical Assembly for Value Chain Networks

Abstract

A dynamic vision system includes a variable focus liquid lens optical assembly. The dynamic vision system includes a control system configured to adjust one or more optical parameters and data collected from the variable focus liquid lens optical assembly in real time. The dynamic vision system includes a processing system that dynamically learns on a training set of outcomes, parameters, and data collected from the variable focus liquid lens optical assembly to train one or more machine learning models to recognize an object.

Claims

1. A dynamic vision system comprising: a variable focus liquid lens optical assembly; a control system configured to adjust one or more optical parameters and data collected from the variable focus liquid lens optical assembly in real time; and a processing system that dynamically learns on a training set of outcomes, parameters, and data collected from the variable focus liquid lens optical assembly to train one or more machine learning models to recognize an object.

2. The dynamic vision system of claim 1 wherein the variable focus liquid lens assembly is continuously adjusted by the control system based on environment factors and on feedback from the processing system to generate an object concept.

3. The dynamic vision system of claim 2 wherein the object concept includes contextual intelligence about the object and its environment and provides superior object recognition by the dynamic vision system.

4. The dynamic vision system of claim 1 wherein a first machine learning model is used to optimize collection of signals by the variable focus liquid lens optical assembly and a second machine learning model is used to operate on the signals to achieve a desired vision outcome.

5. The dynamic vision system of claim 1 wherein the processing system receives real-time adjustable data streams from the variable focus liquid lens optical assembly to generate situational awareness or create out-of-focus images of the object so as to capture rich metadata and contextual intelligence about the object and its environment.

6. The dynamic vision system of claim 1 wherein the control system and the processing system are integrated with the variable focus liquid lens optical assembly.

7. The dynamic vision system of claim 1 wherein the optical parameters adjusted by the control system include at least one of focal length, specularity, color, environment, and lens shape.

8. The dynamic vision system of claim 7 wherein adjustment of the optical parameters result in a change to at least one of spherical aberration, field curvature, coma, chromatic aberration, distortion, vignetting, ghosting, flaring, and diffraction.

9. The dynamic vision system of claim 1 wherein: the processing system is configured to learn on a set of outcomes, parameters, and data from the variable focus liquid lens optical assembly to derive a configuration of the liquid lens optical assembly and the configuration includes at least one of liquid lens materials, geometry, shape, optical properties, performance, and design.

10. The dynamic vision system of claim 1 wherein the machine learning models are embodied on a semiconductor chip that is integrated into a device or system that houses the variable focus liquid lens optical assembly.

11. The dynamic vision system of claim 1 wherein: the machine learning models are pre-trained on a separate system, such as in a cloud computing environment, such as using a large training data set of visual information and/or outcomes, to perform a set of machine vision tasks, and the pre-trained machine learning models are deployed on a device or system that includes the variable focus liquid lens optical assembly.

12. A dynamic vision system comprising: an image processing system configured to collect data from a variable focus liquid lens optical assembly; and an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the variable focus liquid lens optical assembly to recognize an object.

13. The dynamic vision system of claim 12 wherein the artificial intelligence system is configured to learn on a training set of outcomes parameters, and data collected from the variable focus liquid lens optical assembly to control the optical assembly to optimize the collection of data for processing by the artificial intelligence system.

14. A vision system for dynamically learning an object concept about an object of interest, the vision system comprising: a variable focus liquid lens assembly; a control system configured to adjust one or more optical parameters of the variable focus liquid lens assembly in real time; one or more vision sensors configured to capture real-time pixel array based on data received from the variable focus liquid lens assembly in response to adjustments by the control system, wherein the pixel array represents the object concept; and an adaptive intelligence system configured to process the object concept to build a three-dimensional representation of the object, wherein the adaptive intelligence system includes: a machine learning system configured to input the object concept into one or more machine learning models, wherein the object concept is used as training data for the machine learning models; and an artificial intelligence system configured to make classifications, predictions, and other decisions relating to the object, including determining position, orientation, and motion of the object.